Abstract : Over the last two decades, much effort has been devoted to accurately measure Bidirectional Reflectance Distribution Functions (BRDFs) of real-world materials and to use efficiently the resulting data for rendering. Because of their large size, it is difficult to use directly measured BRDFs for real-time applications, and fitting the most sophisticated analytical BRDF models is still a complex task. In this paper, we introduce Rational BRDF, a general-purpose and efficient representation for arbitrary BRDFs, based on Rational Functions (RFs). Using an adapted parametrization we demonstrate how Rational BRDFs offer (1) a more compact and efficient representation using low-degree RFs, (2) an accurate fitting of measured materials with guaranteed control of the residual error, and (3) an efficient importance sampling by applying the same fitting process to determine the inverse of the Cumulative Distribution Function (CDF) generated from the BRDF for use in Monte-Carlo rendering.